Freelancers using Spring Boot in BengaluruFreelancers using Spring Boot in Bengaluru
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Prabhat Kumar's avatar
Prabhat Kumar
Bengaluru, India
Java Engineer Building AI Automations & Integrations
New to Contra
Java Engineer Building AI Automations & Integrations
Cover image for AI Document Intelligence & Invoice
AI Document Intelligence & Invoice Processing Platform Description Built an AI-powered document intelligence platform designed to automate invoice processing, document classification, data extraction, and approval workflows. The system uses AI, OCR, and workflow automation to process business documents automatically, eliminating manual data entry and reducing processing delays across finance and operations teams. By integrating with existing databases and business systems, the platform transforms unstructured documents into actionable business data. Key Features • AI-powered document analysis • Invoice data extraction • OCR-based document processing • Automated approval workflows • Purchase order matching • Vendor management integration • Document classification • Data validation system • Real-time processing dashboard • Automated reporting and audit trails Business Impact ✓ Reduced manual data entry ✓ Faster invoice processing ✓ Reduced processing errors ✓ Improved financial visibility ✓ Faster approval cycles ✓ Reduced operational costs ✓ Increased productivity across teams Technology Stack • Java • Spring Boot • PostgreSQL • OpenAI API • OCR Processing • REST APIs • Workflow Automation • Analytics Dashboard Results • Automated document processing workflows • Reduced invoice processing time by approximately 75% • Improved data accuracy • Reduced manual administrative effort • Accelerated approval and payment cycles This solution demonstrates how AI-powered document intelligence can automate finance and operational processes while improving accuracy, compliance, and efficiency.
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Cover image for AI Lead Enrichment & CRM
AI Lead Enrichment & CRM Automation Platform Built an AI-powered lead enrichment and CRM automation platform designed to help sales teams identify high-quality prospects, enrich lead data automatically, and streamline outreach workflows. The platform combines AI, external data sources, CRM systems, and workflow automation to reduce manual research while improving lead quality and sales efficiency. Key Features • Automated lead enrichment • Company and contact research • AI-generated personalized outreach emails • CRM synchronization • Lead scoring system • Sales pipeline automation • Contact validation • Automated follow-up workflows • Multi-source data aggregation • Analytics and performance tracking Business Impact ✓ Reduced manual lead research ✓ Increased sales team productivity ✓ Improved lead quality ✓ Faster prospect qualification ✓ Higher outreach efficiency ✓ Better CRM data accuracy ✓ Increased pipeline visibility Technology Stack • Java • Spring Boot • PostgreSQL • OpenAI API • REST APIs • CRM Integrations • Workflow Automation • Analytics Dashboard Results • Reduced lead research time by approximately 80% • Automated prospect enrichment process • Improved CRM data quality • Increased sales team efficiency • Faster lead qualification workflows This solution demonstrates how AI can automate prospect research, improve lead quality, and accelerate sales operations.
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Cover image for AI Customer Support Assistant Built an
AI Customer Support Assistant Built an AI-powered customer support platform designed to automate customer interactions, reduce support workload, and provide instant assistance using company documentation and knowledge base content. The system leverages OpenAI, enterprise knowledge bases, and backend automation to deliver accurate, context-aware responses while seamlessly escalating complex issues to human agents when needed. Key Features: • OpenAI-powered conversational assistant • Knowledge base search and retrieval • FAQ automation system • Context-aware customer responses • Human escalation workflow • Multi-channel support integration • Customer interaction analytics • Real-time response monitoring • REST API architecture • Enterprise-grade backend services Business Impact: ✓ Reduced repetitive support workload ✓ Faster customer response times ✓ 24/7 automated customer assistance ✓ Improved customer satisfaction ✓ Consistent support experiences ✓ Lower operational costs ✓ Increased support team efficiency Technology Stack: • Java • Spring Boot • PostgreSQL • OpenAI API • REST APIs • Docker • Maven • Knowledge Base Integration Results: • Automated approximately 80% of common support requests • Reduced average response time from hours to seconds • Reduced manual support workload by approximately 60% • Improved scalability without increasing support staff This solution demonstrates how AI-powered customer support systems can improve customer experience while significantly reducing operational overhead.
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Cover image for AI Business Operations Automation Suite Built
AI Business Operations Automation Suite Built a centralized AI-powered automation platform designed to streamline internal business operations and eliminate repetitive manual work. The system automates workflows across departments including operations, finance, customer support, reporting, and administration. By integrating AI, APIs, databases, and business tools, the platform significantly reduces operational overhead while improving efficiency and accuracy. Key Features: • Automated invoice processing • AI-powered document analysis • Internal workflow automation • Approval and task management system • Automated report generation • Email and notification automation • CRM and database integration • Real-time analytics dashboard • Role-based access control • Custom business process automation Business Impact: ✓ Reduced manual operational workload ✓ Faster processing of business tasks ✓ Improved team productivity ✓ Reduced human errors ✓ Centralized operational visibility ✓ Scalable automation infrastructure Technology Stack: • Java • Spring Boot • PostgreSQL • OpenAI API • REST APIs • Workflow Automation • Dashboard Analytics This solution demonstrates how AI and automation can transform traditional business operations into efficient, scalable, and data-driven workflows.
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Spring Boot(4)
Ashutosh Pandey's avatar
Ashutosh Pandey
Bengaluru, India
Java Backend Developer | Spring Boot & Microservices |
New to Contra
Java Backend Developer | Spring Boot & Microservices |
Cover image for Conceptual architecture of an enterprise
Conceptual architecture of an enterprise public-safety backend platform built around secure, scalable, event-driven microservices. The architecture illustrates the flow from client applications and devices through the API and security layers into Java/Spring Boot microservices, with Keycloak handling authentication, authorization, and token-based security. Core backend services include Client Activation, OIDC XCAP, Core Management, CAT, Subscriber Management, Communication, Notification, and Integration services, with RabbitMQ supporting asynchronous event-driven communication and XDM providing centralized data-management capabilities. The platform also integrates notification channels and external systems while supporting reliable backend responses, integrations, data synchronization, and distributed service workflows. Technologies: Java, Spring Boot, Microservices, REST APIs, Keycloak, RabbitMQ, XDM, Docker, Git, SQL and distributed backend systems.
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Cover image for BDO – Digital Banking Platform
BDO – Digital Banking Platform | Send Money & Bills Payment Contributed to the design and development of core banking services for a digital banking platform, with a focus on Send Money and Bills Payment capabilities. Designed and developed Java/Spring Boot microservices supporting end-to-end transaction workflows. The Send Money and Bills Payment solutions followed a receiver–consumer service model, providing clear separation between request handling, validation, transaction processing, and asynchronous processing. The Receiver services handled request validation, business validations, data validations, beneficiary/biller validations, and other eligibility and business-rule checks before requests were passed for processing. The Consumer services handled the actual transaction execution using Spring Boot transactional processing, maintaining transaction integrity and supporting reliable status and error handling. Worked with Apache Kafka and AWS SQS for asynchronous messaging, event processing, and reliable communication between backend components. The services used MySQL for transactional and application data and were deployed on AWS infrastructure. My responsibilities included backend service design, Java/Spring Boot development, microservices implementation, business and data validation, transaction processing, database integration, messaging workflows, debugging, testing, and production-oriented enhancements. Technology: Java • Spring Boot • Microservices • Apache Kafka • AWS SQS • MySQL • AWS
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Cover image for DummyLabs – E-Commerce Platform |
DummyLabs – E-Commerce Platform | Java, Spring Boot & Microservices Designed and developed a modular e-commerce platform using Java, Spring Boot, Microservices, and MySQL, covering core customer and administrative workflows. The platform included functionality for product management, customer registration and login, product browsing, cart management, order processing, inventory management, and checkout workflows. A major focus of the development was the Admin Portal, providing secure administrative access and capabilities for managing products, users, orders, inventory, and platform data. Developed backend microservices with clear separation of responsibilities, implemented REST APIs, integrated database operations with MySQL, and worked on business logic, data validation, and service-level integrations. The project also involved improving existing backend code for readability, maintainability, and modularity, along with database optimization through SQL queries and stored procedures and ORM-based persistence using Hibernate. Technology: Java • Spring Boot • Microservices • MySQL • Hibernate • REST APIs • AWS
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Cover image for Standard Chartered – Unified Digital
Standard Chartered – Unified Digital Onboarding Platform | Hong Kong & Mainland China Contributed to the backend development of a digital onboarding platform supporting customer journeys across Hong Kong and Mainland China. The platform was developed using Java, Spring Boot, Microservices, GraphQL, Azure, MySQL and Oracle, providing backend services for customer onboarding, application processing, account and product workflows, document management, verification, application tracking, and enterprise integrations. Worked extensively with GraphQL APIs and Java/Spring Boot microservices, developing backend functionality, business logic, service integrations, and application enhancements within a distributed architecture. Contributed to improving code reusability, maintainability, modularity, and separation of responsibilities through object-oriented design patterns and microservices-based development. The platform connected customer-facing onboarding applications with backend services and enterprise systems, supporting secure and scalable digital account-opening and onboarding workflows across the supported regions. Technology: Java 17 • Spring Boot • GraphQL • Microservices • Azure • MySQL • Oracle • REST APIs
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Spring Boot(3)
Soumabha Roy Chaudhuri's avatar
Soumabha Roy Chaudhuri
Bengaluru, India
Fractional CTO | Software Architect | SaaS | AI Agents
Fractional CTO | Software Architect | SaaS | AI Agents
Cover image for 90M registered users · 17
90M registered users · 17 countries · 99.99% uptime · $451M disbursed via DBT Led Everwell Hub from a monolith to a horizontally scalable microservices platform (Java/Python, Docker/Kubernetes, GCP, CI/CD, IaC). As chief architect I personally designed the service decomposition; as CTO I led ~50 engineers plus system-integrator partners and the WHO/Ministry of Health partnership. Deployed across 17 countries and scaled India's national TB platform (Ni-kshay) to ~90M registered patients and staff, with 6 lakh+ direct users, at 99.99% uptime, sub-second P95 latency, and 2h RTO / 4h RPO disaster recovery. The payments module disbursed $451M through direct benefit transfers. Released the platform as MIT open source with full wiki, runbooks, and API contracts — adopted by partner health systems since.
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Cover image for 10x throughput · Kafka ·
10x throughput · Kafka · 13 social channels · built for viral-scale message bursts Redesigned an enterprise social platform's data layer into an event-driven architecture on Apache Kafka, ingesting and analysing real-time social data from 13 channels. Sized for viral-scale bursts of 250–1,000 messages/minute per customer, with hybrid delivery paths: streaming (~15–20s average latency) and polling (~2 min), with a worst-case 5-minute latency ceiling. Also set architecture standards across application, data, and AI, and rebuilt the React/TypeScript frontend for multilingual workspaces with automated WCAG 2.2 / ADA Section 508 accessibility checks. End-to-end throughput improved 10x. Confidential client engagement.
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Cover image for Cold start: 17 min →
Cold start: 17 min → under 3 min. Shard loading: 16 min → 50 sec. Serving cost: ~1/6 of a managed SageMaker equivalent. Performance-engineered a LLaVA vision-language deployment on AWS as part of a specialised strike team, with the full write-up published on LinkedIn (linked under Completed Work). Reduced end-to-end cold start from ~17 minutes to under 3 (66%) via custom Deep Learning AMIs (−32% immediately), ephemeral-storage model caching with parallel aria2c downloads (checkpoint loading 16 min → 50 sec), and 4-bit NF4 quantization (shard loading 41s → 18s). Along the way, diagnosed a storage-path bug where checkpoint shards kept re-downloading despite being baked into the AMI.
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Cover image for Cut shipping time 40% with
Cut shipping time 40% with a production multi-agent system built around governance, not demos. Confidential client engagement. Designed and deployed a multi-agent system covering the full product lifecycle: PRD generation → system design → multi-repo execution → code review → compliance/security checks → release management. Shipping velocity improved 40% across cross-functional teams. Built on a Backstage-based engineering knowledge base with MCP connectors to JIRA, GitHub, Slack, and Teams; LLM workloads on OpenAI and Anthropic via A2A-style agent orchestration, implemented in Python/Bash tooling. Shipped with an enterprise AI governance layer: hallucination detection with knowledge-base remediation, model drift monitoring, and audit logging for regulated environments.
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Spring Boot(1)
Adithya Ga's avatar
Adithya Ga
Bengaluru, India
Full-stack dev | Clean modern UI | AI Powered | Deployment
Full-stack dev | Clean modern UI | AI Powered | Deployment
Cover image for Focus Flow: Revolutionary Educational Technology Platform
Focus Flow: Revolutionary Educational Technology Platform
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Cover image for Telecom Network Inventory Management System Development
Telecom Network Inventory Management System Development
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Cover image for ✨ Powerful & Intuitive CMS Solution
✨ Powerful & Intuitive CMS Solution
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Spring Boot(2)
Umme Hani's avatar
Umme Hani
Bengaluru, India
Full-stack developer turning messy ideas into fast, function
New to Contra
Full-stack developer turning messy ideas into fast, function
Cover image for Rental Marketplace
Rental Marketplace
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Cover image for API Key Management & Rate Limiting Service
API Key Management & Rate Limiting Service
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Cover image for DevOps Capstone Template
DevOps Capstone Template
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Cover image for Multi-Container Application Deployment
Multi-Container Application Deployment
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Spring Boot(2)
Ravi prasath's avatar
Ravi prasath
Bengaluru, India
Full Stack Developer
Full Stack Developer
Cover image for Claims Inspection Engine
Claims Inspection Engine
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Cover image for Payment Processing System
Payment Processing System
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Cover image for AWS Deployment
AWS Deployment
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Spring Boot(2)
Vibin V's avatar
Vibin V
Bengaluru, India
Freelance Web Developer
Freelance Web Developer
Cover image for Movie Booking Website : An
Movie Booking Website : An interactive movie ticket booking platform with dynamic UI, movie listings, and simulated seat selection for a real-world user experience.
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Cover image for Real-Time AI Chat Application: An
Real-Time AI Chat Application: An advanced messaging system developed using React and Spring Boot. I integrated a locally hosted Mistral 7B LLM, allowing users to chat with an AI that has distinct personalities and tones.
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Cover image for Medical Billing Website: A web-based
Medical Billing Website: A web-based medical billing system to manage patient records, generate invoices, and track payments efficiently with a clean and responsive interface.
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Cover image for A production-ready application built with
A production-ready application built with React and Django. It features a Python-based scoring algorithm that evaluates resumes against job descriptions to help candidates improve their chances of getting hired.:
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Spring Boot(2)